Strategic Projects Lead, Safety

Handshake•Seattle, WA

2d•$160,000 - $160,000•Remote

About The Position

As a Strategic Projects Lead (SPL), Safety, you will own the execution of large-scale human data programs that directly power frontier AI model training and evaluation. You will design, build, and execute operational workflows supporting model policy annotation and develop evaluations across a range of policy areas. You will use model policy annotation to help inform model training, evaluation, and enforcement decisions across leading AI systems. Working hands-on with leading AI labs and technology companies, you will make real-time decisions that affect revenue, margins, delivery quality, and long-term customer relationships. This is a high-ownership, outcomes-driven role for operators who thrive in ambiguity, move fast with incomplete information, and are accountable for results at scale.

Requirements

2+ years of experience in trust and safety, policy enforcement, regulatory compliance, regulatory compliance, risk management, management consulting, government or related field
Strong analytical and first-principles problem-solving skills applied to scaling operations; proficiency in SQL (or similar) to draw insights from large data sets
Exceptional communication and stakeholder management skills, including with senior customers
High ownership mindset with pride in end-to-end accountability
Curiosity and ability to quickly learn technical AI concepts and industry trends

Nice To Haves

Experience in scaling policy enforcement or content review workflows across large, distributed workforces
Subject matter expertise in high severity policy harms, such as violent activities, dangerous organizations / individuals, or sexual activities
Experience developing evaluations for harmful content or policy enforcement use-cases

Responsibilities

Design and architect annotation frameworks and labeling workflows that scale effectively while maintaining high precision, accuracy, and inter-rater agreement
Lead, mentor, and manage a team of trusted annotators, fostering a culture of precision, consistency, and care given the sensitive nature of the work while addressing complex edge cases, and identify policy inconsistencies
Collaborate with policy leads to offer organized insights regarding gaps, classification ambiguities, and nuanced scenarios derived from practical data annotation
Construct and iterate on detailed annotation playbooks and auditor resources to drive precision and alignment across diverse datasets and regulatory domains
Detect and surface novel data trends, systemic labeling errors, and strategic opportunities to harden and mature internal safety policies
Partner directly with frontier AI labs and senior stakeholders to shape scope, resolve issues, and expand model policy programs through execution